This study integrated remotely sensed data, geographic information system (GIS), and classification tree-based modeling to delineate ecological units for the Ashley National Forest. Data points , provided by the Ashley National Forest, with a known location and dominant vegetation type, were related to data layers that were determined to be helpful in a landtype classification. These layers included elevation, slope, aspect, potential solar irradiation, precipitation, geology, basins, Landsat thematic mapper (TM) bands 3, 4, 5, and 6, and basic land cover. These points, with their related information, were then used to train the tree-based model for landtype classification. This resulted in a set of rules, in the form of a binary decision tree, that could be applied to the entire study area. After the landtype classification was obtained, it was cross-classified with geology to produce a landtype association layer. This resulting data layer was compared to an existing landtype association map and it was determined, by cross-tabulation, that the two classifications identified many of the same patterns.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-7611 |
| Date | 01 May 1997 |
| Creators | Swiatek, Teresa H. |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
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